1. Introduction
Due to the recent global concerns of climate change, land evaluation has become an increasingly important topic in agricultural research worldwide [
1]. Land evaluation is an essential process in determining how to use a variety of agricultural land areas in the most effective way. This includes considerations in terms of economic, as well as environmental, and also in terms of livelihoods among various social demographics within a given area. This is based on the predictions of land performance over time and under specific uses [
2,
3]. The land evaluation should be conducted in a comprehensive way that takes into account the specific conditions of each research site. Academic institutions and individual researchers around the world have been working for many years to find appropriate ways to apply the methods of the land evaluation approach [
4,
5,
6,
7]. Some of the approaches that can be listed are as Multi-Criteria Decision Analyses (MCDA), based on the Analytic Hierarchy Process (AHP) within the framework of Land Evaluation of Food and Agriculture Organization (FAO), Land Capability Classification, Paramedic Indices, Empirical, and the Ideal Point approach [
1,
8]. Among these listed above, the AHP approach is still the most commonly applied method for land evaluation, especially in regard to specific study sites, with a specific land use type [
9,
10]. Some findings of previous researchers show that [
11,
12] the AHP method still has some limitations. Those are that the opinions of participants are subjective, and the evaluation process requires that the decision-maker express the participants’ preferences on a numeric scale. Moreover, there is often uncertainty in the weighting of criteria and the scoring of some specific attributes of each criterion. The AHP can tend to lack the ability to delineate between consequential vagueness in judgments that occurs during the conversion of verbal scales into numeric scale [
13]. To overcome these limitations, a version of AHP, in combination with Fuzzy theory, has become common alternative in this type of research. These comnined techniques have been termd the Fuzzy Analytic Hierarchy Process (FAHP). Recent research found that the integration of Fuzzy and AHP helps to ensure the accuracy of the MCDA process [
14,
15]. Concerning land evaluation for agricultural land use, Gunal et al. (2022) found that FAHP combined with Geographical Information Systems (GIS) methods is an effective means by which to make decisions in agricultural land use planning [
16]. Many Fuzzy AHP methods have been proposed by variety of researchrs based on the Fuzzy set theory, which was developed by Zadeh in 1965 [
17,
18]. The Fuzzy theory has been developed and integrated successfully into support systems for agriculture, such as that of determining nitrogen balance in the soil [
19]. An interval judgment for the participants’ opinions in a given study was added to the calculation process, instead of having a fixed value. The common membership functions of a Fuzzy theory set were linear, triangular, and trapezoidal [
20,
21]. Among these, Triangular Fuzzy Numbers (TFNs) were preferred because of their simplicity to calculate and, also their usefulness in expressing and processing fuzzy logic. Therefore, many authors have used FAHP with TFNs to construct fuzzy pair-wise comparison matrices [
22,
23].
In recent years, the advancement of GIS technology in combination with certain mathematical models, has allowed for optimal use of data resources to evaluate land suitability in a comprehensive way that can include multiple factors. It provides assistance for statistics, analysis, planning, and management in both spatial and attribute databases [
24,
25]. Because of this development, the spatial data and soil characteristics stored in GIS are easier to develop into user-friendly automatic land evaluation tools [
26]. The integration of GIS and MCDA for agricultural land evaluation has been applied by many researchers worldwide [
27,
28,
29,
30]. This integration is an excellent spatial analysis tool that facilitates the establishment of a comprehensive spatial database involving multi-criteria methodologies in land evaluation [
16]. Therefore, the FAHP and GIS can be an effective method to enhance the accuracy of land suitability evaluation for a particular crop product [
31].
Acacia
(Acacia mangium ×
Acacia auriculiformis) is the most important tree in agricultural production in mountainous regions of Vietnam, especially in Central Vietnam [
32]. Acacia plantations have emerged as an important resource for supporting the rural economy and national export revenue [
33]. In the year 2015, Vietnam established 1.2 million ha of acacia plantations for wood production and more than half of these plantations were cultivated by small farms [
34]. In Thua Thien Hue province, acacia has increased rapidly since the early 1990s due to scientific trials that have shown that the fast-growing nitrogen-fixing species of acacia could be readily grown on degraded soil even though it was previously an alien species to the areas in the question [
35]. In 2006, acacia plantations covered more than 14% of the total land area in Thua Thien Hue province. The hybrid species between
Acacia auriculiformis and
Acacia mangium is the most popular in Central Vietnam in general and in Thua Thien Hue in particular. This is mainly due to the acacia tree’s fast growth and short rotation period, its ability to improve degraded land, and its potential to be developed into multiple products [
36]. In Thua Thien Hue Province, acacia plantations can be cultivated along side protected natural forests in order to improve the livelihoods of local peoples as well as to increase forest cover, but also to allow damaged natural forests to regenerate without further exploitation [
37].
Acacia plantations can have both negative and positive impacts within various areas. It is a land-use type that can potentially restore nutrient cycling in degraded soil but is highly invasive wherever it is planted [
38]. Acacia plantations determination should be carefully undertaken in both methods and databases. However, although land evaluation is a popular process in agricultural land use studies, applying this process for acacia plantations is still rare. In Indonesia, Samsuri et al. (2019) have used 14 land characteristics to identify the land suitability for acacia in a region of North Sumatra, with more than 80% of the total area having the highest level of suitability [
39]. This research has been conducted by combining the plant growth requirements with specific land characteristics. However, the suitability of each criterion in this research is referenced from the previous academic literature without the participation of land users who have a detailed experiential knowledge of the growth patterns of acacia on their lands. In Vietnam, several recent pieces of research have been conducted in relation to land evaluations for acacia. Nguyen et al. (2019) used five physical soil criteria in the AHP model to evaluate the suitability of each land unit for acacia plantations [
40]. This research also creates a linear regression between land suitability and acacia yield. In the same year, Ronja et al. (2019) also used the AHP method to assess the suitability level of acacia plantations in the mountainous district of Central Vietnam [
9]. Most of the above research has been carried out by the Boolean method and therefore needs to be included with other methods for comparison.
The cultivation of acacia in the mountainous regions of Thua Thien Hue Province still needs long-term strategic planning because the existing acacia plantation areas were planted based on farming experience and the subjective inclinations of individual households. These unpredictable factors disrupt the stability of the acacia wood market in general and cause harmful effects on existing production activities, especially for the mountainous regions. For example, planting acacia in inappropriate places leads to low economic efficiency. Therefore, our study was conducted in Nam Dong district, Thua Thien Hue Province, with the aim of (i) comparing the results of the land evaluation for acacia by the AHP method and FAHP method, (ii) proposing appropriate placements for acacia plantation in Nam Dong district.
4. Discussion
Previous research has already established the impact of the physical criteria on the development of acacia in Thua Thien Hue. Ho Thanh Ha (2013) stated that there are significant influences of soil type, soil texture, soil depth, and slope on acacia yield in 36 communes in Thua Thien Hue Province [
66]. In our research, soil depth is the most important criterion for acacia plantations. This finding is consistent with research conducted in Indonesia in 1999 [
67] which found that soil depth is most strongly correlated to the productivity of acacia among the three variables of soil depth, soil reaction, and horizon depth. As reported in some studies, acacia species have high root density concentrated at a soil depth of 0 cm to 150 cm [
68,
69]. Therefore, a thick soil layer is a necessary condition for acacia plantation. A recent study in Thua Thien Hue Province showed that 97% of households planted acacia in plots with a slope of less than 30
0 [
35]. This criterion influences most agricultural activities as it affects the rate of soil degradation, especially soil erosion in mountainous regions [
70]. The soil texture also influences acacia growth in Vietnam, Tran et al. (2020) [
71] stated that there was a negative correlation between the volume of acacia yield and the percentage of loam. A higher number of loam particles leads to more compact soil, which limits root growth because of the difficulty for roots to penetrate, and the limitation of oxygen in the soil. Therefore, the score of sandy loam was highest, followed by loam and clay. Soil type was not an important criterion in the selection process of acacia planting areas; however, the participants agreed that alluvial soil is the most suitable because the soil quality of this kind of soil is better than other soils in Nam Dong. Our research is consistent with other researchers who found that the acacia yield in areas with fluvisols soil is the highest compared to other soils in Thua Thien Hue Province [
66]. The soil pH has the lowest influence on acacia plantations. In this research area, the soil pH values range from 4.3 to 5.0, meaning that the soil is very acidic. In Vietnam, soil pH under acacia plantations is generally lower than other land-use types such as pasture, abandoned, and secondary forests [
72,
73]. Land users and agricultural agencies in Vietnam do not pay much attention to soil acidity in the process of acacia plantations. In the technical manuals for acacia cultivation published by the Ministry of Agriculture of Vietnam, there is no mention of soil acidity analysis, nor do they recommend solutions to reduce acidity for acacia plantations [
74]. Growing acacia can cause soil acidity, which has become increasingly common in recent years [
75]. Especially for the weathered soil in the wet tropics, acacia plantations are shown to be a cause of soil acidification due to the cations in the soil that are translocated into the biomass of the acacia [
76]. Concerning SOC content, Trieu et al. (2016) [
73] found that the SOC content of acacia plantations ranges from 1.1% to 3.9%, with SOC in the northern and southern parts of Vietnam being higher than in the Central region. Our research found that the SOC content in Nam Dong district is lower than 2% of soil weight which concurs with other recent studies concerning this area [
77,
78]. In addition to endemism due to the nature of the soil type, farming practices can also cause low SOC levels, especially in acacia-growing areas. According to a previous study, burning the accumulated litter of vegetation surface from the previous year’s cultivation is a common technique in preparing land for acacia plantations in Thua Thien Hue. This practice also causes a reduction in SOC content [
79]. It has also been noted that the cultivation of acacia, if conducted correctly, will increase the amount of SOC significantly, especially the hybrid acacia species [
79]. In addition, recent research found that the soil organic matter in coarse soil within the fifth year of the second rotation of acacia plantations is significantly higher than in the seventh year of the first rotation and the second year of the second rotation [
80]. The land evaluation result by FAHP methods indicated that the soil type is not an important criterion in the decision on the acacia plantations in the Nam Dong district. This finding is consistent with previous research, which found that acacia is grown in a wide range of soil types, especially in Central Vietnam [
33]. There is concern about the extent of the criteria used for land evaluation for agricultural purposes, many researchers suggested that climatic conditions need to be considered as evaluated criteria. Acacia planting sites in Vietnam are at 8° to 22° N and have an elevation of 5 to 500 m. The suitable climatic conditions, the precipitation is 1500 to 2500 mm, and annual temperature is from 23° to 28° C [
81]. Our research site is small and within suitable climatic conditions for acacia plantations; therefore, in this research, we did not consider these criteria. However, for other regions, the climatic conditions need to be included in the land evaluation process.
This research did make a comparison of the effectiveness of the Fuzzy-set and Boolean approaches. However, further analysis needs to be carried out regarding these aspects. In the early 1990s, significant research indicated that the Fuzzy set approach provided more gradual results than the Boolean approach in land evaluation for land suitability [
82,
83]. Many studies show that FAHP is more effective than AHP. Additional research is needed to establish the significant factors contributing to these two methods’ differences. [
84]. In the AHP approach, uncertainty factors are not mentioned, and the answers are more categorical than in FAHP; therefore, with AHP, the experts who are questioned must have an excellent knowledge of their subject and be proficient as well as careful with their responses [
85,
86]. In the case of an uncertain or” fuzzy” environment, fuzzy numbers have to be used for the evaluation due to the deviations of decision-makers [
86,
87]. Another study that corroborates our findings between the two modalities is Rodcha et al. (2021) [
18], which stated that the FAHP is better than the AHP method in land evaluation for cash crops such as eucalyptus in Thailand with an overall accuracy of 80% compared to 71%. The FAHP provides better land evaluation results than the AHP method because the fuzzy scale does not use integer values, and it is more flexible than the AHP scale because it has small fractions between 0–1.
Based on the coefficient of determination between the predicted yield and the observed yield, the hypothesis is further confirmed that the FAHP is more suitable than AHP in land evaluation for acacia plantations in the mountainous regions in Central Vietnam. This suitability may be because there are inconsistencies in the qualifications of fifteen of the participants in our research, a critical factor in these discrepancies being that the members of this group each have different backgrounds and professions. This variable is an inherent weakness of the focus group discussion method. It is unavoidable that the link between people’s perceptions and their socio-cultural situation is critical to decision-making on natural resources [
48]. Therefore, it is imperative to find creative and effective ways of reaching a consensus among the various stakeholders in the areas concerned. Recent research indicated that the homogeneity of participants might help promote discussion and exchange, giving cohesive viewpoints that represent shared context, but it cannot apply to projects that aim to support a broad range of users [
88]. The groups that are too diverse may pose a different set of problems leading to difficulty in achieving a satisfactory conclusion to the topic [
89]. Therefore, in selecting participants for focus group discussion, homogeneity of background among participants is recommended, while conversely, and at the same time, diverse attitudes within the group are beneficial in covering the more obscure aspects of the given subject [
90]. The FAHP is more capable of reconciling differences of opinion in the group based on linguistic variables, converted into triangular fuzzy numbers, as compared to the treatment of numerical data such as in the AHP method. Moreover, the variation in opinions will have less impact on the final result due to the lower bound created by TFNs. These findings were also corroborated by Rodcha et al. (2019) [
18], who found that in the FAHP model, some factors can be eliminated due to their decreased significance without any effect on the overall results. Thus, individual studies can determine the number of factors to use in the model. In our research, the data from
Figure 4 indicates that the weighting of soil pH and soil types by FAHP is less significant than those by AHP. The soil characteristics are continuity and variation factors since the FAHP is a helpful method for land evaluation, especially in agricultural production [
91]. The FAHP method can increase the accuracy of land evaluation results by 4.62% in comparison to the original AHP method based on six selected criteria in this research. The characteristics of most of these criteria are clearly expressed as quantitative data; therefore, the differences in the evaluation of participants are not as significant.
A comparison with the current land use map shows that the acacia plantations in Nam Dong district still have shortcomings, as only 1277 hectares out of 3102 hectares of high suitability class are used for acacia. The remaining area is mainly planted with rubber and rice, with an area of 1540 ha and 164 ha, respectively. From 2000–2010, rubber latex prices were very high, and people could harvest all year round, so many households focused on developing rubber plantations in the Nam Dong district [
92,
93]. The conversion of natural forests to rubber plantations was perpetrated by rubber companies and individual farmers with the encouragement of certain local government bodies [
94]. Because rubber prices have decreased in recent years [
46], the area of new rubber plantations has not increased. However, due to previous planting practices, local farmers continue to keep these rubber plantations. Recent research indicated that after several rotations of rubber cultivation, the quality of the 0–10 cm soil layer was deficient, with an increase in SOC thermal stability [
95]. In addition, the acacia wood market has greatly expanded worldwide to facilitate the demand for furniture production [
96]. The contribution of acacia cultivation to household income is increasingly significant [
97,
98,
99]. Therefore, in the future, as the need for rubber plantations continues to decrease in viability, local authorities need to have plans to convert from rubber cultivation to acacia plantations. However, it is necessary to invest in a system of wood factories and logistics to ensure product output for the local farmers. The difficulties due to terrain, poor infrastructure, and the limited number of wood processing companies, the travel time from the villages to the plantations, and the distance from acacia plantations to processing firms continue to be significant limitations for the development of acacia plantations in Nam Dong [
46]. In the areas that show non-suitability for acacia cultivation but yet are currently planted with acacia, we found that most of these areas have a thin soil layer. Local farmers planted acacia in these areas with too much density. Farmers tend to harvest these acacia areas in the 4th year instead of waiting until the 7th year when the acacia wood has the most significant biomass and economic value. Wood products in these areas are often of poor quality and, therefore, cannot be processed into valuable furniture but can only be used for export in the form of wood chips. Farmers still grow acacia because they have not had the guidance for cultivating more profitable crops in the long run in these areas. It is possible to implement intercropping with short-term crops such as peanuts, cassava, or lemongrass for these areas. This farming model has been successfully implemented in Thanh Hoi commune in the North of Vietnam [
32]. In Thua Thien Hue province, the model of intercropping acacia with cassava has been implemented in some districts, such as A Luoi (2%), Phu Loc (16%), and Huong Tra (20% of total areas). Cassava is often intermixed with newly planted acacia seedlings during the first year after tree harvesting [
35].
Acacia plantation is the most viable means of a prosperous livelihood for farmers within the mountainous regions of Central Vietnam. The reasons are that it is highly suitable for the local topographical conditions, its high yield over a short period, and the low cost of start-up [
33,
46]. In Nam Dong, acacia cultivation accounts for over one-fourth of the revenue for farmers, contributing 1451 USD to an average household farm income of 4415 USD. This income from acacia plantations is higher than other forest and agricultural cultivation in the area and thus creates a positive correlation to the farm scale [
46]. Moreover, acacia plantations can improve many aspects of the bio-physical environment, especially by preventing soil erosion and improving soil fertility through nitrogen fixation [
95]. In addition, in Vietnam, there are programs combining acacia and beekeeping. According to a report by JICA, with a scale of about 1200 hectares in a commune in the North of Vietnam, there were 82 beekeepers interspersed within existing acacia plantations and produced an amount of honey totaling 3198 L [
100]. In Thua Thien Hue province, due to the weather characteristics, it often rains a lot from September to November every year, so it is necessary to consider moving bee colonies to acacia plantations at a suitable time. Because of these factors, land users and decision-making should establish future mandates to expand the areas of acacia plantations. This can be conducted by implementing the re-grouping of lands and land use policies.
5. Conclusions
In this study, six physical soil characteristics of agricultural land areas were selected for land evaluation for acacia plantations in Nam Dong district, Thua Thien Hue Province, central Vietnam, using the AHP and FAHP methods. The ranking of criteria in both methods is the same, but the weighting of each criterion is different. Using the FAHP method, we found that soil depth has the highest priority, with a value of 0.32, but using the AHP method, even though soil depth still has the highest priority, the value is 0.28. Overall, soil depth and slope play an essential role in acacia plantations, followed by SOC, soil texture, soil pH, and the various soil types. This finding indicates that land users need to consider investing in SOC enrichment and also in reducing soil acidity to enhance the effectiveness of acacia plantations at the research site.
The land suitability map was performed by integrating MCDA and GIS technology, showing four suitability classes for acacia plantations in the Nam Dong district. The most suitable areas for growing acacia are concentrated in the valleys, where the soil layer is more than 70 cm thick and the slope is less than 15 degrees. This map is the result of land evaluation based on six physical soil characteristics, and therefore it would be a valuable reference document for agricultural land use planning. For other purposes, e.g., regional master planning or economic development projects, integration with other databases or expansion to other land use criteria are required.
The FAHP method is a practical and suitable approach for land evaluation, especially for agricultural land. This method has advantages and flexibility in converting qualitative to quantitative opinions based on the upper and lower bounds of the triangle of fuzzy numbers. As land evaluation is a complex process involving the participation of many stakeholders, including local government, agricultural scientists, farmers, and other partners in the agricultural value chain, we suggest that FAHP should be used for land evaluation, together with additional social and economic criteria, and also in consideration with other kinds of crop plantations within Vietnam. This combination is more meaningful in the context of sustainable land use in mountainous regions where appropriate agricultural land use is essential in improving the livelihoods of ethnic minority groups and mitigating systemic poverty.
The limitation of this research was that only physical soil criteria for land evaluation were considered, while there are additional criteria that should be considered to have a more comprehensive understanding in regard to the effectiveness of land use in these areas. While the criteria focused on for this study are valuable and relevant in their own right, in regard to future studies, it would be of additional value to include socio-economic factors within the criteria in order to provide a complete land use scenario to serve specific local demands. In addition, it is beneficial to compare the current hierarchical analysis methods with some other contemporary techniques in agricultural land assessment, especially the modern machine learning-based approach.